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Robust Adaptive Back-stepping Control Using Dual Friction Observer and RNN with Disturbance Observer for Dynamic Friction Model (외란관측기를 갖는 RNN과 이중마찰관측기를 이용한 동적마찰모델에 대한 강인한 적응 백-스테핑제어)

  • Han, Seong-Ik
    • Transactions of the Korean Society of Machine Tool Engineers
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    • v.18 no.1
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    • pp.50-58
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    • 2009
  • For precise tracking control of a servo system with nonlinear friction, a robust friction compensation scheme is presented in this paper. The nonlinear friction is difficult to identify the friction parameters exactly through experiments. Friction parameters can be also varied according to contact conditions such as the variation of temperature and lubrication. Thus, in order to overcome these problems and obtain the desired position tracking performance, a robust adaptive back-stepping control scheme with a dual friction observer is developed. In addition, to estimate lumped friction uncertainty due to modeling errors, a DEKF recurrent neural network and adaptive reconstructed error estimator are also developed. The feasibility of the proposed control scheme is verified through the experiment fur a ball-screw system.